(network, input)

(network, loss, loss_prime, x_train, y_train, epochs = 1000, learning_rate = 0.01, verbose = True)

(x, y, limit)

(x, y, limit)

(self)

(self, output_gradient, learning_rate)

(self, input)

(x)

(self, input_shape, kernel_size, depth)

(self, input_shape, output_shape)

(self, input_size, output_size)

(self)

(self)

(self, activation, activation_prime)

(self, output_gradient, learning_rate)

(self, output_gradient, learning_rate)

(self, output_gradient, learning_rate)

(self, output_gradient, learning_rate)

(self, output_gradient, learning_rate)

(y_true, y_pred)

(y_true, y_pred)

(self, input)

(self, input)

(self, input)

(self, input)

(self, input)

(y_true, y_pred)

(y_true, y_pred)

(x)

(x)

(x)